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- All Subjects: Obesity
Obesity is a significant national public health crisis, affecting one-third of American adults. It is a complex and multifactorial disease that increases the risk of multiple chronic medical conditions including coronary heart disease, diabetes, and even leading to potential premature mortality. Moreover, increased health care utilization and escalating medical costs associated with obesity treatment are overwhelming an already burdened health care system. Obesity is nondiscriminatory, affecting individuals from various demographic and socioeconomic backgrounds, even extending to our unique population of active duty military service members and veterans.
Despite mandatory physical fitness and body composition requirements, active duty service members continue to experience an increasing prevalence of obesity. The obesity epidemic has considerable implications for military readiness, accession, and retention. Limited studies have examined weight-loss interventions including self-paced and provider-led interventions among active duty military service members with varying degrees of success. The purpose of this evidence based doctoral project was to examine the effectiveness of a twelve-week group lifestyle intervention involving education regarding healthy diet, physical activity and behavior change recommendations on weight and body mass index (BMI). The study demonstrated no significant differences in initial and post intervention weight and BMI.
Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.
To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.
This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.
This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.
This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.
PowerPoint presentation to the Santa Fe Institute, October 2004.